# from resnet import resnet18

# import torch
# from thop import profile
# # 增加可读性
# from thop import clever_format
# inputs = torch.rand(1,3,240, 240)
# model = resnet18(num_classes=27249)

# flops, params = profile(model, inputs=(inputs, ))
# flops, params = clever_format([flops, params], "%.3f")

# print('flops:', flops)
# print('params:', params)
# print('Total params: %.2fM' % (sum(p.numel()
#                                        for p in model.parameters()) / 1000000.0))



block = [1,4,56,7]

print(block.expansion)